Abstract
Access to reliable and accurate bathymetric data is fundamental to many marine activities. This paper proposes a merge-normalization (MN) method that is suitable for multisource bathymetric data fusion in deep ocean areas, to solve the problem of difficult to integrate high-precision digital bathymetric model (DBM) for complex sources and various resolutions of global deep ocean bathymetric data. Then we apply it to the DBM construction of the Mariana Trench. The method combines multibeam, single-beam, and electronic navigational chart data with Shuttle Radar Topography Mission (SRTM) dataset by using the workflow of merging and normalizing, which can fill the data gaps while preserving topographic details in high-resolution bathymetric data. Compared with the widely used General Bathymetric Chart of the Oceans (GEBCO) dataset, the Mariana Trench dataset constructed in this study demonstrated improved accuracy, resolution, and topographic detail, highlighting the value of the application of the method and of its development potential.
Highlights
Accurate and reliable bathymetric data is the basis of marine activities
IMPLEMENTATION OF MN DATA FUSION METHOD According to the above steps, the multisource bathymetric data were fused to construct the digital bathymetric model (DBM) of the Mariana Trench
The topographies are flat and the topographic details are disappeared, which show that the DBM obtained by the MN multisource bathymetric data fusion method preserves a lot of high-resolution topographic details
Summary
Accurate and reliable bathymetric data is the basis of marine activities. A high-resolution digital bathymetric model (DBM) can be used for the construction of charts and for the study of geomorphological features and genesis, seabed tectonic processes, marine resources, hydrodynamic flow models, biological habitats, and ecosystems [1]–[4]. The accuracy of multisource data from the same area is evaluated using the mean difference [16] based on the central beam soundings of multibeam swath-bathymetric data as follows. The principle of the surface fitting algorithm is as follows: the seabed surface is fitted according to the beam points, the depth differences between the measured bathymetric data and the surface are calculated, and the outliers are eliminated by incorporating error processing theory.
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